sensor_spec — OPTICS scene op

Data kinds: nonetable (an op determined by its arguments alone — it takes no image or data input)

Call: import optscene; optscene.sensor_spec(pixel_um: 'float' = 3.45, resolution=(1024, 1024), quantum_efficiency: 'float' = 0.6, full_well_e: 'float' = 10000.0, read_noise_e: 'float' = 2.5, dark_e_per_s: 'float' = 5.0, bit_depth: 'int' = 8, gain_e_per_unit: 'float' = 50000.0, shutter: 'str' = 'global', model: 'str' = None) -> 'dict' (or opsoptics.get("sensor_spec"))

Usage

An image sensor's specification. It holds only the values on the side that decides the number of electrons.

> The detailed description below is the original text — the summary and the headings are translated.

`quantum_efficiency は光子 -> 電子の変換効率、dark_e_per_s` は暗電流

(暗視野は露光が長いのでここが効く)、`shutter` は global / rolling

(コンベア上の部品では rolling の歪みが出る)。

光学的な明るさ(何個の光子が来るか)はレンズとレイアウトで決まり、ここでは

それをどう記録するかだけを持つ ―― 混ぜると「センサーを変えたのに視野も

変わった」ような追跡不能な変更になる。

`model に実在の型番(sensor_catalog()` のキー、例 "IMX541")を渡すと、

解像度・画素ピッチ・シャッタに加えて **QE・読み出し雑音・飽和容量も

Basler の EMVA1288 実測**で埋まる(引数で明示した値はそちらを優先)。

出所はカメラ実測なので、別のカメラなら少し変わる。

Family-wide input contract (fail-closed)

Every optics op validates its input before computing (nothing slips through silently):

Units are baked into the argument name_mm / _um / _deg / _mrad. Confusing mm with µm does not crash; it yields a plausible-looking wrong answer, so the name prevents it. Nothing here guesses the unit from the magnitude.

• **Strings raise ValueError** — float('50') succeeds, so an unparsed configuration value would slip through as a length (measured: thin_lens('50', '200') returned a plausible 66.667 mm). bool is refused too, as the implicit promotion True == 1.

• **complex / masked arrays raise ValueError (real-valued slots only; silently dropping the imaginary part or peeling off the mask is refused). NaN/Inf raises ValueError on every input.**

Division by zero and its relatives are refused by name: focal length 0, radius of curvature 0, refractive index <= 0, a fully opaque aperture (all zeros, so the normalisation is 0/0), a PSF whose sum is <= 0, a Stokes vector with S0 = 0, and an object sitting at the front focal point (the image is at infinity).

Only two ops return a non-finite value, and both state it as a contract: depth_of_field returns far_mm = inf beyond the hyperfocal distance (that is what the hyperfocal distance means), and gaussian_beam returns wavefront_radius_mm = inf at the waist (the radius of curvature of a plane wavefront). Both also return a finite companion (far_is_infinite / curvature_per_mm). **Any other silent NaN/Inf is detected internally and raises ValueError** — "float64 overflowed" and "the answer is infinite" are different claims, so the first is never returned wearing the face of the second.

Size caps: generated grids are capped by optics.MAX_GRID (4096); supplied fields/PSFs/apertures by optics.MAX_FIELD_ELEMENTS (2^24); ABCD element chains by optics.MAX_SYSTEM_ELEMENTS (1024); Zernike by MAX_ZERNIKE_TERMS (512) / MAX_ZERNIKE_ORDER (40) / MAX_ZERNIKE_BASIS (2^25). This closes, fail-closed, the paths where a small argument triggers a huge internal allocation (measured: n_max=40 × 4096² needs 108 GB).

Physically impossible states are refused too: a Stokes vector with degree of polarisation > 1, negative transmittance, negative intensity, and invalid Zernike indices such as n-|m| odd.

Detailed usage guide

optics_imaging family guide

Background guides (the physics and conventions behind this op)

dataset_conventions — 学習データセット規約の知識 — COCO / YOLO / VOC と外観検査での落とし穴

mv_cameras — 産業用カメラメーカー(センサとの紐付け・ラインスキャン / TDI)

mv_illumination_practice — 照明の実務知識 — 波長・偏光・点灯方式・外光・安全

mv_image_sensors — 産業用イメージセンサ(現行品中心)

virtual_machine_vision — 仮想マシンビジョン — パラメータの洗い出しとオブジェクト模型

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

vision_layout_from_catalogpy -3.11 examples/vision_layout_from_catalog.py

Ops the type connects to (they accept table as input)

abcd_matrix · wavefront_stats · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd · spot_diagram

Same category (scene)

scene_material · scene_plane · scene_sphere · scene_box · scene_cylinder · surface_defect · surface_finish · random_defects


*Provenance: optscene.py — OPTICS operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.